Note: Descriptions are shown in the official language in which they were submitted.
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SYSTEM AND METHOD TO SIMULATE AND MANAGE A WIRELESS
LOCAL AREA NETWORK (WLAN)
BackQrLound of the Art
s Computer and telecommunication networks, specifically wireless networks,
have grown in size and complexity. Both of these factors have caused network
designers, operators, and users to rely on modeling software to assist them in
simulating network configurations to optimize performance. Conventionally,
network simulations have been used to evaluate performance of network
io configurations under defined traffic conditions. Performance includes such
objective criteria as response time, throughput, and costs of transmissions.
Recently, the focus of network trends have turned to the wireless local area
networks (WLANs). As the popularity of WLANs continues to increase, the
deployment density of IEEE 802.11 access points (APs) and the number of client
~s stations has also increased.
This overall increase of IEEE 802.11 radios brings about new challenges for
the administrator of an IEEE 802.11 network. Without proper tools, managing
the
radio environment of an IEEE 802.11 network becomes very difficult.
Administrators are plagued with the problem of effectively deploying WLANs and
2o subsequently managing the network in the face of other radio interference,
as well
as IEEE 802.11 network congestion.
The WLAN administrator is primarily concerned with providing a reliable
network with adequate coverage at the highest level of throughput. In order to
accomplish this, the administrator today must employ expensive site surveys
prior
2s to deployment in combination with costly monitoring tools and personnel
expenses
used to maintain the network. Even after providing expensive site surveys, the
administrator is still plagued with a slow detection of radio network problems
and
substandard means of malting radio network additions or modifications.
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Essentially, the optimization of a WLAN is a complex problem. A WLAN is
far more dynamic than legacy wired networks. The required timeliness to tune
the
performance of a WLAN to an optimum is very short.
Although unmanaged and non-optimized WLAN deployments may provide
s basic functionality, the user experience may greatly erode with the
introduction of
new wireless traffic. For example, wireless traffic frequently occurs with the
wide
deployment of WLAN based voice clients (WVOIP).
In this example, in order to achieve acceptable audio quality in WVOIP,
problems may occur in that the WLAN may not be able to handle the data traffic
to required of the network. Conversely, WVOIP clients may be denied access
(e.g.
get a busy signal) in order to preserve bandwidth for data clients.
Even without WVOIP, some installations could find they have unacceptable
data handling capacity. Other problems occur due to factors such as poor
positioning of the APs, newly installed neighboring APs, increased user
density,
is new widely used wireless applications, and the like.
Many parameters affect the performance of a WLAN. For example, these
parameters include the selection of an AP's frequency band, power levels,
protocol
settings and shifting client associations between APs. Because of this
complexity,
conventionally, it has been extremely difficult to analytically determine
acceptable
2o algorithms that converge to optimized solutions.
The highly dynamic nature of a WLAN not only makes the network
optimization more demanding than ever, but also requires the procedure to
reach an
optimization very quickly. Optimization speed may be the single most important
requirement.
2s Reaching the optimal performance of a WLAN by adjusting WLAN
configurations in real-time is unrealistic because of the significant amount
of time
it takes to iterate to an optimal performance. Moreover, adjusting WLAN
configurations in real-time may adversely affect the WLAN performance during
the process of optimization (e.g. spiral into a performance null).
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Conventionally, deterministic approaches utilizing management software
alone cannot accurately predict the effect of changes on a WLAN. Even people
with significant experience in the field of WLANs cannot accurately predict
the
affect of these changes. Therefore, it is unfeasible for a WLAN management
tool
s alone to provide optimized solutions for a WLAN optimized configuration.
Thus, what is needed is a combined simulation/management means to quickly
and accurately determine the effect of given parameter changes before they are
applied, or to gather historical usage and performance data and use the
gathered
data to better optimize system parameters.
to h1 other words, what is needed is a system and method to combine the
functionality of a WLAN simulation tool with a management software system to
create a model-based system. A system suitably configured to apply Discrete
Event Driven MAC protocol simulations to a wireless network management
situation in a real time fashion thereby enabling administrators to better
optimize
is the performance of WLANS is needed.
Summax-~of the Disclosed Embodiments
In accordance with one embodiment, an article of manufacture embodied in a
computer-readable medium for use in a processing system for modeling
configurations of a wireless local area network is provided.
2o One embodiment of the article of manufacture includes a characteristic
receiving logic for causing the processing system to determine a set of
original
characteristics of the wireless local area network. As well, a simulation
logic for
causing the processing system to simulate an outcome based upon the set of
original characteristics in accordance with a goal. In other embodiments, the
goal
2s may be user defined or based upon historical data.
Further, a configuration creation logic for causing the processing system to
create a set of new configuration based upon the outcome and a management
logic
for causing the processing system to apply the set of new configuration to the
wireless local area network are included within the article.
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In another embodiment, the simulation logic of the article is a discrete event
simulation logic. Alternately, an analysis logic for causing the processing
system
to determine if the outcome satisfies the goal is provided.
In yet another embodiment, the simulation logic includes a simulation
s execution logic for causing the processing system to simulate a WLAN based
on
received network characteristics and a set of configurations with Discrete
Event
Simulations. Likewise, a prediction logic causes the processing system to
predict
effects (e.g. total throughput, noise mitigation, access point loading and
voice/data
distribution) on the wireless local area network based upon the simulation
results.
io Optimization logic for causing the processing system to optimize the set of
new configurations based upon the goal and simulation results is further
provided
with respect to an alternate embodiment. The algorithm can be any searching
algorithm known in the art including, but not limited to, Newton's method or
Gradient Search.
Is Yet another embodiment provides for a display logic for causing the
processing system to display a graphical representation of the outcome.
Brief Description Of The Drawings
It will be appreciated that the illustrated boundaries of elements (e.g.
boxes,
groups of boxes, or other shapes) in the figures represent one example of the
2o boundaries. One of ordinary skill in the art will appreciate that one
element may be
designed as multiple elements or that multiple elements may be designed as one
element. An element shown as an internal component of another element may be
implemented as an external component and vice versa.
Figure 1 is a system block diagram of a system in accordance with a disclosed
2s embodiment.
Figure 2 illustrates one embodiment of a methodology for adjusting and/or
reconfiguring a WLAN in accordance with a disclosed embodiment.
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Detailed Description Of Illustrated Embodiments)
The following includes definitions of selected terms used throughout the
disclosure. The definitions include examples of various embodiments and/or
forms
of components that fall within the scope of a term and that may be used for
s implementation. Of course, the examples are not intended to be limiting and
other
embodiments may be implemented. Both singular and plural forms of all terms
fall
within each meaning:
"Computer-readable medium", as used herein, refers to any medium that
participates in directly or indirectly providing signals, instructions and/or
data to
one or more processors for execution. Such a medium may take many forms,
including but not limited to, non-volatile media, volatile media, and
transmission
media. Non-volatile media may include, for example, optical or magnetic disks.
Volatile media may include dynamic memory. Transmission media may include
coaxial cables, copper wire, and fiber optic cables. Transmission media can
also
~s take the form of acoustic or light waves, such as those generated during
radio-wave
and infra-red data communications, or take the form of one or more groups of
signals. Common forms of computer-readable media include, for exaanple, a
floppy disk, a flexible disk, hard dislc, magnetic tape, or any other magnetic
medium, a CD-ROM, any other optical medium, punch cards, papertape, any other
2o physical medium with patterns of holes, a RAM, a PROM, an EPROM, a FLASH-
EPROM, any other memory chip or cartridge, a carrier wave/pulse, or any other
medium from which a computer, a processor or other electronic device can read.
Signals used to propagate instructions or other software over a networlc, such
as the
Internet, are also considered a "computer-readable medium."
2s "Logic", as used herein, includes but is not limited to hardware, firmware,
software and/or combinations of each to perform a functions) or an action(s),
and/or to cause a function or action from another component. For example,
based
on a desired application or needs, logic may include a software controlled
microprocessor, discrete logic such as an application specific integrated
circuit
30 (ASIC), a programmable/programmed logic device, memory device containing
instructions, or the lilce. Logic may also be fully embodied as software.
s
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"Signal", as used herein, includes but is not limited to one or more
electrical
signals, analog or digital signals, one or more computer or processor
instructions,
messages, a bit or bit stream, or other means that can be received,
transmitted,
and/or detected.
s "Software", as used herein, includes but is not limited to one or more
computer readable and/or executable instructions that cause a computer or
other
electronic device to perform functions, actions, and/or behave in a desired
manner.
The instructions may be embodied in various forms such as objects, routines,
algorithms, modules or programs including separate applications or code from
io dynamically linl~ed libraries. Software may also be implemented in various
forms
such as a stand-alone program, a function call, a servlet, an applet,
instructions
stored in a memory, part of an operating system or other type of executable
instructions. It will be appreciated by one of ordinary skill in the art that
the form
of software may be dependent on, for example, requirements of a desired
is application, the environment it runs on, and/or the desires of a
designer/prograrnmer or the like.
"User", as used herein, includes but is not limited to one or more persons,
software, computers or other devices, or combinations of these.
h1 one embodiment, a combination simulation/management modeling system
2o and method to adjust the performance of a wireless local area networlc
(WLAN) is
provided. Specifically, in one embodiment, a combined simulation/management
system and method is provided that may be configured to apply Discrete Event
Driven MAC protocol simulations to a wireless network management in a real-
time
fashion.
2s It will be appreciated by one slcilled in the art that optimizing a WLAN
within
a simulated environment, instead of the real-world network environment, may
permit the required optimizing speed without adversely affecting the network
performance before an optimal solution is obtained.
The present system and method combines a simulator with the management
3o software. Therefore, the present system and method may eliminate the need
for a
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user or administrator to have specific knowledge about WLAN environments and
protocols.
As discussed herein, in accordance with the present system and method, once
defined goals are input into the system the simulator and management tools
s artificially develop WLAN parameters and characteristics to accomplish the
goals.
Once developed, the WLAN parameters and characteristics may be applied by the
management tool to the WLAN.
Illustrated in FIG. 1 is a simplified component diagram of one embodiment of
the present system and method. Specifically, FIG. 1 illustrates a block
diagram of
a system 100 including a WLAN management tool component 110, a simulation
tool 120 and an interface module 130 operatively connected to permit the
management tool component 110 to communicate with the simulation tool
component 130. Finally, illustrated in FIG. 1 is a WLAN 140 operatively
1s connected to WLAN management tool component 110 whereby the WLAN
management tool component 110 is suitably configured to adjust the WLAN 140 in
accordance with parameters generated by the simulation tool component 120.
In operation, the combination simulation/management system 100 may be
suitably configured to quickly and accurately determine the effect of desired
2o parameter changes (e.g. goal(s)) before they are applied. This
determination may
be accomplished via the WLAN simulation tool 120. Additionally, the system 100
may be configured to gather historical usage and performance data and use the
gathered data to better optimize system parameters of the WLAN 140 in
accordance with user defined goals.
2s Of course, it will be appreciated that the goals may be pre-programmed in
order to conform to a specified parameter or set of parameters. For example,
the
system 100 may be programmed to achieve maximum coverage regardless of the
data rate in order to maximize throughput.
Continuing with the example, the system 100 may be suitably adapted to apply
3o Discrete Event Driven (DED) MAC protocol simulations via the simulation
tool
120 in a real-time fashion to assist administrators to adjust and potentially
optimize
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the performance of the WLAN 140. It will be appreciated by one skilled in the
art
that any suitably capable management and simulation tool known in the art may
be
used in connection with the present system.
With reference to the simulation tool 120, the high speed Cisco DES (Discrete
s Event Simulator) WLAN simulation tool may be employed in accordance with the
system described herein. An artisan will appreciate that the DES is written in
C++
and is capable of simulating a WLAN 140 in real-time. Further, DES may be
configured to accurately simulate the industry standards (e.g. IEEE 802.11
protocols) and may be readily enhanced to conform to new user defined
1 o requirements.
Moreover, the DES may be suitably configured to simulate the WLAN 140
environment with regard to a vast number of characteristics (e.g. WLAN
configurations). For example, the DES is suitably configured to simulate
characteristics and configurations, including, but not limited to, terms of
~s propagating effects, noise, transmit power, receiver sensitivity, adjacent
channel
interference or the like.
Additionally, it will be appreciated that the DES simulation tool of one
embodiment provides a simulation environment directed to an IEEE 802.11 MAC
protocol with C++. DES is configured to discern the impact of a PHY layer
design
20 or change in a wireless device on the MAC layer performance. For example,
DES
is capable of determining WLAN coverage range versus data rates. As well, DES,
is capable of determining the WLAN capacity in terms of throughput of a multi-
channel AP when channel interferences axe significant.
2s Although the simulation environment targets the PHY layer's impact on the
MAC layer, it will be appreciated that DES has the potential to be used in
other
areas such as MAC protocol trade-offs and power save algorithm analysis. For
example, in a wireless voice over lP application, simulations built with DES
are
capable of successfully predicting the WLAN capacities under various
3o configurations, as well as the packet loss and delay characteristics.
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Turning now to the management tool 110, in addition to utilizing of any
capable WLAN simulation tool such as DES, it will appreciate that any WLAN
management tool known in the art may be used in accordance with the present
system. For example, the Cisco network management program may be used. It is
s noted that WLAN management tools and software are configured to simplify the
management and control of a WLAN 140 by providing a single point of control
for
an administrator or user to configure and/or adjust parameters of a WLAN.
Thus, together with the extremely fast simulation speed of the DES simulation
tool, a network management program may be empowered as a WLAN management
1o tool in order to make predictable adjustments to WLAN parameters. As well,
a
network management program may be used in connection with DES to use
historical information to do the same and perhaps to employ specific settings
tailored to hourly daily traffic and enviromnent conditions.
With a high speed WLAN simulation tool 120 such as the Cisco DES, the
~5 WLAN 140 may be optimized quickly through a simulated WLAN environment
rather than within the operating network. It will be appreciated that this
approach
allows for the optimization speed required by the dynamic nature of the WLAN
140 without running the risk of adversely affecting the WLAN 140 performance
during the procedure of optimization. Of course, it will be appreciated by one
2o skilled in the art that the present system 100 utilizes a WLAN simulator
tool 120
(e.g. Cisco DES) that is fast enough to process the simulation to meet
predefined
goals.
Referring back to the example, as illustrated in FIG. 1, in order to implement
the approach, an interface module 130 is used in connection with the WLAN
25 management tool 110 to interface with the WLAN simulator tool 120. The
interface module 130 may be suitably configured to send network configurations
and/or performance statistics between the WLAN management tool 110 and the
WLAN simulator tool 120. It will be appreciated that the network
configurations
and performance statistics may be any user defined characteristics (e.g.
goal(s)).
3o For example, the characteristics may be AP loading statistics and/or based
upon
user defined preferences, historical network data or the like.
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The simulator tool 120 may be suitably configured to perform WLAN 140
optimization via simulations based upon a predefined configuration or user
defined
goal. Next, the simulator tool 120 may be configured to send the optimized
configurations back to the management tool 110 via interface module 130. Upon
s receipt, the management tool 110 may be suitably configured to apply the new
configurations to the WLAN 140 accordingly.
It will be appreciated that the simulator tool 120 may be a stand-alone
component or combined into with the management tool 110 and/or interface
module 130. Further, it will be appreciated that the simulation tool 120 may
be
io configured to directly communicate solely with the interface module 130 in
order
to ultimately transfer the new characteristics to the network management tool
110.
Moreover, it will be appreciated that the WLAN simulator tool 120 and the WLAN
management tool 110 are not necessarily co-located. In other words, it will be
appreciated that the management tool 110 and the simulator tool 120 may be
is physically located at different locations and suitably configured to
communicate
with one another via the interface module 130 or other means known in the art
(e.g.
Internet).
In one embodiment, in operation, network characteristics may be transferred
via the interface module 130 from the management tool 110 to the simulation
tool
20 120. Next, by using inputted characteristics from the WLAN management tool
110
corresponding with a predefined goal, the WLAN simulator 120 may be suitably
configured to execute algorithms in order to select new parameter settings
(e.g.
characteristics), and to predict the effect on the WLAN 140 with reference to
many
metrics. For example, the simulator tool 120 may be advantageously configured
to
2s predict metrics such as total throughput, AP loading, voice/data
distribution and/or
the like.
It will be appreciated that the set of optimization parameters (e.g.
characteristics) and/or the optimization target functions (e.g. goals) for
WLAN 140
performance may be user defined to correspond to any user desired criteria of
the
so WLAN 140. As well, an artisan will appreciate that the simulation tool 120
may
be configured to use any applicable optimization algorithm known in the art.
For
example, the simulation tool 120 may be configured to use optimization
algorithms
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such as Newton's method, Gradient Search, Neural Networks, Exhaustive Search
or
the like to resolve optimized parameters.
Of course, it will be appreciated that in accordance with alternate
embodiments, configurations, goals and other parameters may be maintained or
s stored via any computer-readable medium known in the art.
In an alternate embodiment, the system 100 may be suitably configured to
pernlit a user or administrator to develop a policy by selecting any general
network
configuration goal such as maximizing coverage regardless of data rate,
maximizing throughput, or specifying location of a particular AP. Once the
policy
to has been developed by the user or administrator, the simulation tool 120
may be
configured to apply the policy goals against the converging algorithm. Next,
the
results of the new WLAN settings or configurations may be subsequently
inspected
or applied to the WLAN 140.
Yet another embodiment of the present system utilizes a map of the WLAN
is 140 coverage area. Specifically, the map, as viewed via an optional
graphical user
interface (GUI) (not shown), may identify placement of network components
(e.g.
APs) in accordance with the WLAN 140. In accordance with this embodiment, the
GUI (not shown) may be suitably configured to assist a user or administrator
with
the deployment or rearrangement of the network components (e.g. APs).
2o Accordingly, the optional GUI (not shown) used in connection with the
simulation
tool 120 may be configured to visually illustrate the effect of any changes in
WLAN 140 configuration. An artisan will appreciate that the GUI (not shown)
display of predicted results may permit the user to confirm the new
configurations
or to further refine the simulation request.
2s It will be appreciated that in order to assist an administrator or user to
utilize
these new features or characteristics more effectively, the GUI (not shown)
may be
configured to provide a two-dimensional graphical layout of the radio
networlc.
Further, the GUI (not shown) may be configured to allow the user to manage the
WLAN 140 through a more physical view in addition to the existing logical view
3o provided by the management tool 110. As well, the optional GUI (not shown)
may
be configured to display system information, such as radio parameters, alarm
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summary, performance data, as well as rogue-AP's location through the physical
mew.
Illustrated in FIG. 2 is one embodiment of a methodology 200 associated with
a WLAN simulation/management tool in accordance with the present system.
s The illustrated elements denote "processing blocks" and represents
instructions or groups of instructions that cause a processor, mechanism, or
other
device to perform a function, an action, and/or to make a decision.
Alternatively,
the processing blocks may represent functions and/or actions performed by
functionally equivalent circuits such as a digital signal processor circuit,
an
to application specific integrated circuit (ASIC), or other logic device.
The diagram does not depict syntax of any particular programming language.
Rather, the diagram illustrates functional information one spilled in the art
could
use to fabricate circuits, generate computer software, or use a combination of
hardware and software to perform the illustrated processing. It will be
appreciated
is that electronic and software applications may involve dynamic and flexible
processes such that the illustrated blocks can be performed in other sequences
different than the one shown and/or blocks may be combined or separated into
multiple components.
With reference to FIG. 2, the methodology 200 will be described with
2o reference to a method to simulate and manage a WLAN based upon
predetermined
criteria (e.g. user defined goal(s)).
The process is commenced upon identifying WLAN goals (block 210). It will
be appreciated that the WLAN goals may be established via user defined
parameters. As well, the WLAN goals may be any identifiable networlc parameter
2s and may be arbitrary or based upon historical networlc data. For example, a
WLAN goal may be defined to strive to maximize coverage regardless of data
rate
in order to maximize throughput time.
Next, at block 220, the system is suitably configured to receive current WLAN
characteristics and configurations. In other words, in one embodiment, the
current
3o WLAN characteristics and network configurations and/or performance
statistics
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may be retrieved from the management tool by the interface module. Once
retrieved, the current WLAN characteristics and configurations may be
transferred
from the management tool to the simulation tool via the interface module
(block
230).
s Upon receipt of the current WLAN characteristics and configurations, the
system may be configured to create new WLAN configurations based upon
preferred WLAN simulation teclnuques (block 240). It will be appreciated that
any
WLAN simulation technique known in the art may be used without departing from
the spirit and scope of the present system and/or methodology.
to At decision block 250, a query is made to determine if the WLAN goals have
been met by the simulation of block 240. If the desired goals have not been
met,
the system reinitiates the simulation thereby creating new WLAN configurations
(block 240) as illustrated in FIG. 2.
If at decision block 250 the system determines that the WLAN goals have
~s been met via simulation of block 240, the system sends the acceptable new
WLAN
configurations to the management tool (block 260). Finally, at block 270, the
new
configurations are applied to the WLAN thereby prompting reconfiguration
and/or
adjustment of the WLAN in accordance with the new configurations. If at
decision
block 250 the system determines that the WLAN goals have not been met, a new
2o set of configurations will be generated via performing optimizations (block
280).
This new set of configurations will then be sent to block 240 for the next
iteration
of simulations.
As illustrated in FIG. 2, it will be appreciated that the simulation of block
240
may include the steps of: executing simulations (block 275), and predicting
the
?s effect of the new configurations on the WLAN (block 285). Of course, an
artisan
will appreciate the steps included within the simulation bloclc 240.
While the present invention has been illustrated by the description of
embodiments thereof, and while the embodiments have been described in
considerable detail, it is not the intention of the applicants to restrict or
in any way
30 limit the scope of the appended claims to such detail. Additional
advantages and
modifications will readily appear to those skilled in the art. Therefore, the
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invention, in its broader aspects, is not limited to the specific details, the
representative apparatus, and illustrative examples shown and described.
Accordingly, departures may be made from such details without departing from
the
spirit or scope of the applicant's general inventive concept.
14
